In order to perfectly realize a mobile communication system which allows transmission and receiving of all kinds of data with desired peers anytime and anywhere, the 3rd generation mobile communication systems which are operable by global and single standards and provide far better services than the present mobile communication system have been commercialized.
The next generation mobile communication system transmits and receives currently serviced speech signals, video, and other types of data with high reliability. Also, as various services are provided, the bandwidths of transmitted and received data will be wider, and demands of the mobile communication networks will be increased further.
Therefore, the most important technical aim of the next generation mobile communication systems is to propose techniques for transmitting further amounts of data with reliability by using as narrow bandwidths as possible.
However, since the reduction of useable bandwidths and the increase of reliability are incompatible, the conventional arts cannot solve the problems of capacity and reliability required by the next generation mobile communication.
Recently, a new technique for concurrently achieving the increases of capacity and reliability in the communication systems by controlling beam patterns of antennas and suppressing interference and noise has been aggressively studied. The so-called smart antenna technique has been highlighted as the core skill of the next generation mobile communication system.
The smart antenna technique allows a base station to establish an optimized beam to a mobile station subscriber, thereby reducing radio interference, increasing communication capacity, and improving communication quality.
For example, a smart antenna system installed in a base station adaptively processes respective speeds of 1) a fixed target such as an office, 2) a target which moves at a low speed such as a person or a satellite, and 3) a target which moves at a high speed such as a car or a train, and consecutively provides optimized beam patterns to thus provide maximum gains in the target directions, and provides relatively very much fewer gains in other directions to thus suppress the interference. That is, the above-noted smart antenna system increases capacity of the mobile communication system and improves communication reliability.
Therefore, the smart antenna characteristics provide a new technique applicable to the W-CDMA and CDMA2000 which are next generation communication methods for transmitting a huge volume of data with reliability.
Most studies for smart transmit antennas have been focused at the downlink category. In general, it is needed for a base station to know a temporal channel of a downlink in advance in order to apply a closed-loop downlink beam forming technique.
It is needed for the mobile station to feed temporal channel information back to the base station since frequency bandwidths of uplink and downlink channels are different in the FDD (frequency division duplex) mode. In this instance, a large amount of needed feedback information can be a problem for the closed-loop beam forming characteristics.
A conventional blind beam forming technique is a method for measuring an uplink channel and adaptively forming a downlink beam assuming that radio environments and spatial statistical properties of the uplink and the downlink are similar with each other. The blind beam forming technique requires no feedback information since it uses the channels' reciprocity, but loses diversity gain since a beam forming vector does not follow changes of the temporal channel.
Temporal channel information of the downlink must be fed back in order to obtain the spatial diversity gain, and since the amount of feedback information is increased as the number of transmit antennas is increased, and since the feedback rate is increased in order to track the changes of the temporal channel, it is very difficult to apply the above-described beam forming technique to the case in which a large number of transmit antennas are provided or a moving body moves fast. Many techniques for alleviating the above-noted problems have recently been proposed.
Korea Application No. 1999-43679 (filed on Oct. 9, 1999) discloses “Transmit antenna diversity controlling device and method in mobile communication system,” and it relates to a control device and method for adaptively calculating weights in the closed-loop transmit antenna and performing transmit antenna diversity.
In detail, the above-described Korea Application consecutively tracks an optimized weight vector for a predetermined time frame, that is, detects a state of an initial downlink channel to find a weight vector, and finds a further accurate weight vector by using the found weight vector when detecting a state of a subsequent downlink channel, and hence, it applies variable weights to the respective antennas used for the transmit antenna diversity according to the channel states, and calculates the current weight by using the previous weight to thus perform adaptive weight calculation.
Korea Application No. 2000-11617 (filed on Mar. 8, 2000) discloses “Blind transmit antenna array device and method using feedback information in mobile communication system,” and it aims to use at least two antenna elements and corresponding weight vectors and allow a base station to form appropriate transmission beans toward a specific mobile station, and to thereby increase subscriber capacity.
In detail, a base station proposed by the Korea Application No. 2000-11617 comprises a reverse processor for processing reverse signals received through an antenna array; a forward fading information extractor for extracting forward fading information from the received reverse signals; a bean forming controller for generating weight vectors for forming transmission beams by using the forward fading information and the received reverse signals; and a forward processor for forming a transmission message from the transmission beam according to the weight vector, and outputting the transmission message to the antenna array. Also, a mobile station comprises a forward processor for receiving forward signals and processing the sane; a forward fading estimator for estimating forward fading information for each path of the received forward signals; a forward fading encoder for combining the estimated forward fading information for each path to encode the sane; and a reverse processor for multiplexing the encoded forward fading information together with the transmission message, and feeding them back to the base station.
Therefore, the invention of the Korea Application No. 2000-11617 uses a mixed forward beam forming method for selecting from among a default (predictive) bean forming method and a blind forward beam forming method according to the moving speed of the mobile station when a feedback delay time is less or greater in a mobile communication system with multiple paths, and hence, the invention enables receiving the forward fading information from the mobile station and forming a further reliable transmission beam to thereby increase capacity and save transmission power of the mobile station.
A transaction entitled “Exploiting the short-term and long-term channel properties in space and time: Eigenbeam forming concepts for the BS in WCDMA” is disclosed in the European Trans. Telecomm. (pp. 365 to 378, 12th volume, 2001).
The transaction disclosed a temporal and spatial transmitter and receiver in the CDMA system with adaptive antennas applied to a base station according to eigenbeam forming concepts which reduces processing dimensions and finds a mean of a spatial covariance matrix in the downlink by using the long-term channel property, or obtains decorrelated diversity branches in the spatial and temporal manner by separating the spatial covariance matrix of a similar temporal tap in the uplink. US Application No. 2003-144032 (filed on Jul. 31, 2003) discloses “Beam forming method” which proposes a spatial and temporal transmitter and receiver in the CDMA system with an adaptive antenna applied to a base station according to the eigenbeam forming concepts.
In detail, the US Application removes the problems of the long-term eigenbeam formation and the short-term optimal combination which are properties of a rake receiver to thereby reduce calculation complexity, increases minimization of feedback for short-term processing since an eigenrake is adaptive to various radio environments when the number of antennas is increased, and obtains diversity gains and an interference alleviating effect by concurrently using the long-term and short-term properties of the channel.
The eigenbeam forming smart antenna technique proposed for the 3GPP (3rd generation partnership project) standard is realized by feeding back the information required for forming the downlink beans through the uplink, which will now be described.
First, the spatial channel property includes a long-term channel property and a short-term channel property. In this instance, the long-term channel property represents a spatial channel property which is varied in the long-term manner according to correlation between antenna elements, buildings and mountains, and locations of mobile stations, and the short-term channel property represents a spatial channel property which is quickly varied in the short manner depending on the Rayleigh fading.
In general, the short-term spatial covariance matrix RST of the mobile station obtained by using an orthogonal pilot tone transmitted by the base station is given in Math FIG. 1.
                              R          ST                =                              ∑                          n              =              1                        N                    ⁢                                    h              n                        ⁢                          h              n              H                                                          Math        ⁢                                  ⁢        Figure        ⁢                                  ⁢        1            
where hn is a channel vector of the nth temporal tap and is given as hn=(hn1, hn2, . . . , hnL)T, and L is a number of transmit antennas.
Also, the long-term spatial covariance matrix RLT is given in Math FIG. 2.RLT(i)=ρRLT(i-1)+(1-ρ)RST(i)  MathFigure 2
where ρ is a forgetting factor.
The long-term spatial covariance matrix RLT is given in Math FIG. 3 according to eigendecomposition.RLTV=VΘ  MathFigure 3
whereΘ=diag(λ1,λ2, . . . ,λL is a diagonal matrix with eigenvalues ofλ1≧λ2≧ . . . ≧λL as elements, andV=[V1V2 . . . VL]where vL is an eigenvector corresponding to λL.
Also, in order to quickly reduce a lesser amount of feedback or computational complexity, eigenvectors which correspond to Nf large eigenvalues from among L eigen values are defined to be eigenbeams or eigenmodes. The eigenbeam for maximizing a receive power
      P    m    =                    ∑                  n          =          1                N            ⁢                                                            v              m              H                        ⁢                          h              n                                                2              =                  v        m        H            ⁢              R        ST        T            ⁢              v        m            of the mobile station is selected from among the eigenbeams.
In the 3GPP WCDMA system, the eigenbeams are transmitted per bit for each frame to the base station from the mobile station according to the feedback speed of 1,500 bps through the DPCCH (dedicated physical control channel), and when two eigenmodes are provided, it is determined to select one of the two eigenmodes for each slot, and a corresponding result is transmitted to the base station from the mobile station.
However, since the OFDM method has different bean forming vectors for the respective subcarriers in the case of using the 3GPP method, feedback information is substantially increased, and it is impossible to realize the effective communication system.